The invention relates generally to methods for entering text into a computer and, more particularly, relates to providing alternatives for a text selection derived from multiple stochastic input sources.
Computer users have traditionally entered text into word processors through a keyboard and mouse. In recent years, however, word processors have become more sophisticated by allowing users to enter text into them through other input methods, such as speech or handwriting. Although a computer cannot always interpret such input with complete accuracy, a computer can generate a list of text alternatives for the input. Furthermore, the computer can often assign to each alternative a probability that the alternative is the one the user intended. Input that produces such probabilistic results is called xe2x80x9cstochastic input,xe2x80x9d while input that can be accurately determined, such as typed text, is called xe2x80x9cnon-stochastic input.xe2x80x9d
Typically, text produced in a word processor from stochastic input must be heavily edited by the user in order to produce the text intended by the user when he or she created the stochastic input. The editing process has been simplified by allowing the user to select text created from stochastic data and request alternatives for the text selection. In response, the computer can provide the user with alternatives for the text selection through a graphical user interface. If the user chooses one of the alternatives, the computer replaces the text selection with the selected alternative.
Suppose that after a user creates text in a word processor by providing the word processor with stochastic input, such as speech, the user then edits the text. The user may, for example, replace a word of the text with a new word typed into the computer with a keyboard. Current word processors do not incorporate typed text edits into the alternatives they provide for an edited text selection. Thus, there is a need in the art for a method of providing alternatives to edited text derived from stochastic input.
Another problem occurs if the user attempts to request alternatives for a text selection spanning multiple stochastic input sources. For instance, the user may request alternatives for a text selection containing a word based on handwriting input and a word based on speech input. Current word processors are not capable of providing meaningful alternatives for such a text selection. Thus, there is also a need in the art for a method of providing alternatives for a text selection derived from multiple stochastic input sources.
An input method editor (IME) is another word processor input method that produces stochastic data. Generally, an IME converts input into foreign language text. The input into an IME may, for example, be typed text entered into the computer through a keyboard and mouse. An IME is especially useful for creating ideograms in Asian and other languages. Because there are many more ideograms in such languages than there are keys on a keyboard, entering a particular ideogram into the computer typically requires multiples keystrokes, which the IME interprets as a composed character.
In a typical IME, a user may type in English characters defining a phonetic spelling for a desired Chinese character. Since many Chinese characters have similar pronunciations, the typed phonetic spelling may represent any one of a number of different Chinese characters. The IME then provides the user with the most probable candidates corresponding to the typed phonetic spelling so that the user can choose the correct one.
Programmers have previously recognized the value of providing speech input into an IME. This is done by first converting the speech into text, which is then used as input into the IME. As has already been explained, however, the interpretation of speech is stochastic in nature. Hence, the text produced by the speech interpreter may not be the text that was intended by the user. If incorrect text is used as input into the IME, the results produced by the IME are likely to be poor. Accordingly, when speech is used as input into an IME, the program interpreting the speech data typically allows the user to first correct the text produced by the speech interpreter before inputting that text into the IME. When the IME produces foreign language translations of the text, the user may again choose the desired alternative because the result of an IME is also stochastic in nature. Requiring the user to edit the results at two different stages of the process can be inefficient and inconvenient. Thus, there is a further need in the art for an improved method of handling speech input to an IME.
The present invention meets the needs described above in a stochastic input combiner that facilitates the editing of text. The invention does this by providing alternatives for a text selection made by the user, even where that text selection is derived from multiple input sources, one or more of which can be stochastic in nature.
The stochastic input combiner provides the alternatives to the user in list form through a graphical user interface. The user can then choose one of the alternatives to replace the text selection the user has highlighted for editing. This can often be quicker than requiring the user to think of alternatives on his or her own and then make changes accordingly using a keyboard and mouse. If the user does not find an alternative the user likes for the text selection, the user can edit the text selection using the keyboard and mouse. In response, the stochastic input combiner can provide an updated list of alternatives that incorporate the user""s changes. Often, the user need only partially edit the text selection before the stochastic input combiner produces an alternative the user likes, so the stochastic input combiner again improves editing efficiency.
The stochastic input combiner may also provide the advantage of a natural language model. Such a model may analyze the text selection as a whole using natural language principles in order to provide a better list of alternatives for the text selection. This, too, improves the user""s editing efficiency.
Generally described, the present invention includes a method for correcting text. The user first enters text into the computer, perhaps using multiple stochastic input sources. The user may also use a keyboard and mouse to enter text into the computer.
Keyboard/mouse entry of text is an example of an input source which is non-stochastic, meaning that the text intended to be entered through the source can be determined with complete accuracy. On the other hand, a stochastic input source is one that converts input into a list of alternatives, each having less than 100% probability of being the correct alternative. Because speech cannot always be interpreted by a computer with complete accuracy, a speech recognition unit is an example of a stochastic input source which converts speech input into a list of text alternatives. Other examples of a stochastic input source include a handwriting recognition unit and an input method editor (IME). Where an input source for a text component is stochastic, the most likely alternative for the text component is generally used to represent the text component in the text selection.
Once the user enters text into the computer, the user can begin the correction process by making a text selection of a portion of the text the user entered. This text selection can include multiple text components. Such a text component can be a subset of the text selection that the user entered through a single input source. The user may have entered different text components within the text selection using different input sources, and the user may have entered one or more of the text components with a stochastic input source.
Once the user makes a text selection, the user may enter a command to display alternatives for the text selection as a whole. The stochastic input combiner then parses the text selection into its text components and retrieves a stochastic model representing the alternatives for a text component originating from a stochastic input source. This stochastic model may include a list of the alternatives for the text component together with the probabilities associated with the alternatives. Alternatively, the stochastic model may include a lattice.
The stochastic input combiner then combines the stochastic model retrieved with other text components to produce a list of alternatives for the text selection as a whole. The stochastic input combiner then displays this list of alternatives for the text selection on a display device, such as a monitor. The user may then select one of the displayed alternatives. In that case, the selected alternative replaces the text selection.
The stochastic input combiner may also utilize a natural language model. In this alternative, the stochastic input combiner may combine the stochastic models for each stochastic text component to produce an interim list of alternatives for the text selection that the combiner provides to the natural language model. The natural language model forms a revised list of alternatives by reevaluating the interim list of alternatives based on natural language principles applied by the natural language model to the text selection as a whole. The natural language model may also add new alternatives to the revised list of alternatives that are not found in the interim list. After the natural language model returns the revised list of alternatives to the stochastic input combiner, the stochastic input combiner provides the revised list of alternatives for display.
In another alternative, a series of stochastic input sources creates a stochastic text component. This means that at least one stochastic input source produces a stochastic result that serves as input into a second stochastic input source. Typically, the first stochastic input source of the series requires user input, while subsequent stochastic input sources in the series receive an alternative produced by the previous stochastic input source as input. An example of this is a speech recognition unit that produces text used as input into an IME. When stochastic input sources in series produce a stochastic text component, the stochastic input combiner can produce a series stochastic model that contains alternatives for the stochastic text component and accurate probabilities for those alternatives that account for the likelihood of the inputs into each stochastic input source in the series. This process eliminates any need for the user to choose a single alternative produced by a stochastic input source to use as input into a subsequent stochastic input source.
To produce a series stochastic model for a text component derived from a series of stochastic input sources, the stochastic input combiner first submits to the first stochastic input source in the series the user input intended for that stochastic input source. By processing the user input, the first stochastic input source produces a stochastic result. The stochastic result that the first stochastic input source produces has multiple alternatives, and the stochastic input combiner selects that stochastic result. By using each alternative of the selected stochastic result as input into the second stochastic input source to produce a stochastic result for the second stochastic input source, the stochastic input combiner produces multiple stochastic results, each stochastic result having multiple alternatives, for the second stochastic input source. If any stochastic result for the second stochastic input source does not contain an xe2x80x9cn-bestxe2x80x9d alternatives list, the stochastic input combiner converts that stochastic result into an xe2x80x9cn-bestxe2x80x9d alternatives list because converting all stochastic results into the same format simplifies the process of combining them. The stochastic input combiner then combines the stochastic results for the second stochastic input source to create a totalized alternatives list for the second stochastic input source. If there are only two stochastic input sources in the series, then the totalized alternatives list may serve as the stochastic model for the text component resulting from the series.
The stochastic input combiner may also be functional for expanding the scope of correction for a text selection received from a user to a larger text unit. To do this, the stochastic input combiner submits the text selection to a correction scope model to make the determination of whether the scope of correction should be adjusted. In response to submitting the text selection, the stochastic input combiner receives from the correction scope model a text unit that includes the text selection and at least one adjacent word. Using the text unit, the stochastic input combiner can then produce a list of alternatives for the text unit and display those alternatives on a display device.
The various aspects of the present invention may be more clearly understood and appreciated from a review of the following detailed description of the disclosed embodiments and by reference to the appended drawings and claims.